Usually it would be "Master's Thesis" if it's for a masters degree or
"Dissertation" if you're doing it for a PhD. (
http://www.pearsonlongman.com/ae/azar/grammar_ex/message_board/archive/articles/00333.html
).

Isn't English fun? ;)

Ian


On Wed, Dec 4, 2013 at 2:34 PM, Marek Otahal <[email protected]> wrote:

> right on, a thesis :)
> Btw, is "diploma thesis" ever used?
>
>
> On Wed, Dec 4, 2013 at 11:15 PM, Ian Danforth <[email protected]>wrote:
>
>> Diploma? Do you perhaps mean "Thesis?" or "Dissertation?"
>>
>> Ian
>>
>>
>> On Wed, Dec 4, 2013 at 2:13 PM, Marek Otahal <[email protected]>wrote:
>>
>>> hi fellow neurohackers ;)
>>>
>>> ...maybe you could see that coming, I'm working on my diploma on "ALife
>>> agents' Behavior with HTM/CLA - NuPIC";
>>> From my schedule, I'm nearing what I(more like we) could have done
>>> programming-wise, and I'm writing my text now. I am posting the outline
>>> here, would be glad if you could give it a thought and let me know:
>>> -some comments/suggestions on the structure/ordering?
>>> -some topics I definitely must not miss out
>>> -code, benchmarks,pictures,demos, videos are always welcome!
>>> -anything else I'm missing, doin' wrong?
>>>
>>> Please try to keep it to the Requirements which I'm bound to focus on.
>>>
>>> This help is really appretiated!
>>>
>>> Thanks a ton,
>>> Forever yours, breznak ;)
>>>
>>> PS: forgive the scarcity and cryptic sentences, it's just my notes to
>>> "kick in the thought.."
>>>
>>>
>>>
>>> ===Architecture of Autonomous Agent Based on Cortical Learning
>>> Algorithms===
>>>
>>> Instructions & requirements:
>>> *) Study the fundamental principles of Cortical Learning Algorithms
>>> (CLA) inspired by mammalian brain.
>>> *) Modify these algorithms to be able to produce also behaviour, aside
>>> of learning.
>>> *) Implement CLA (or augment a current implementation) with ability to
>>> produce behaviour. This
>>> implementation should support Robotic Operating System (ROS)
>>> communication and should be as domain
>>> independent as possible.
>>> *) Compare the efficiency of resulting learning and behaviour of agent
>>> controlled by this modification of
>>> CLA with another today used learning and decision making techniques.
>>>
>>> ========================
>>> Abstract
>>>
>>> Intro
>>>
>>> Principles of mind & brains:
>>> -intro
>>> -approaches
>>> --neurolevel - LIF, Hodg-Huxley, BlueBrain initiative, ..,
>>> POV-synapses/neurons/reqions/knowledge
>>> --psychological - memories, emotions, un/supervised learning
>>> --computional & hw - assumptions, domains, simplifications, HW
>>> (memristor), processing power exp..
>>> --philosophical - what are memories, can machines think?/learn?/sense?,
>>> how do we learn, perceive?
>>> --future prognosis - AI domains conquered, being tackeled, still miles
>>> away; IBM/Watson, (big)data-mining, memristors,
>>>
>>> Theory of HTM/CLA
>>> (resources mostly Whitepaper, OnIntelligence, ML, videos, Fergal's blog)
>>> -SDR
>>> -CLA region
>>> --column,cell,synapse
>>> --SP
>>> --TP
>>> -HTM
>>> --links
>>>
>>> Producing behavior:
>>> (resources mostly Vitku, Kadlec, psychology)
>>> -action learning - sensomotory behav - SDR-pattern-matching, compare
>>> with planning (LISP)
>>> -memory - short term, long term, compare with other AI approaches to
>>> achieve that (LTST-Mem), HTM sequences, ?Q "how are memories stored in
>>> brain?", neuron fields, deepnets
>>> -emotions! - goal, drive, implementations (low level hardcoded),
>>> -forgetting - automatic in CLA region, missing values, outliners,
>>> -attention - anomaly detection! - "staring at crippled ppl",
>>> -abstraction
>>> -high level concepts
>>> -language - CEPT, current SotA
>>>
>>> Implemention of CLA - NuPIC
>>> (resources ML, community)
>>> -my former experiments (htm java)
>>> -why i ended up with NuPIC:
>>> --comunity
>>> --history
>>> --implementations - other htm/cla-like projects
>>> --projects! - hackatlons, all the cool stuff ppl do!
>>> --ROS! - impl, connection to other research
>>> --domain indipendence! - encoders, parameters (swarming), areas of what
>>> can be done (see projects), what is problematic/incomplete currently
>>> --things left TODO -hierarchy,vision domain, strip down impl,
>>> --tools - swarming, cerebro, serialization, benchmarking, VMs
>>>
>>> Compare efficiency of CLA-based learning and behavior with another AI
>>> technique used for that matter
>>> (help, any practical benchmarks??)
>>> -RL, NN, SOM, RNN, prerequisite&effect based programming(LISP),
>>> -benchmarks - CLA resistance to noise (SDRs)
>>>             - sequences
>>>             - ability to generate behav in a natural sense
>>> -where is CLA ruling at the time?
>>> -where is it losing?
>>>
>>> Conclusion
>>> -what has been achieved
>>> -what's left
>>> -possible future research directions
>>>
>>> Appendix A - Demos
>>> "a (theoretical) proof-of-concept examples to sections above"
>>>
>>>
>>>
>>> --
>>> Marek Otahal :o)
>>>
>>> _______________________________________________
>>> nupic mailing list
>>> [email protected]
>>> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
>>>
>>>
>>
>> _______________________________________________
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>>
>>
>
>
> --
> Marek Otahal :o)
>
> _______________________________________________
> nupic mailing list
> [email protected]
> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
>
>
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